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Preparation and characterization of high-reactivity explosive-based nano-boron microspheres

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PARTICUOLOGY 2024年第10期93卷 125-136页

作者： Dong, Chen Wang, Yi Jia, Kanghui song, Dan song, Xiaolan An, Chongwei North Univ China Sch Mat Sci & Engn Taiyuan 030051 Peoples R China Jinxi Grp Shanxi Jiangyang Chem Co Ltd Taiyuan 030051 Peoples R China China Ordnance Inst Sci & Technol Beijing 100089 Peoples R China North Univ China Sch Environm & Safety Engn Taiyuan 030051 Peoples R China

Boron nanoparticles, with their remarkably high gravimetric and volumetric calorific values, emerge as the most promising fuel in energetic fields. However, challenges such as susceptibility to oxidation, high ignition temperature, and low combustion efficiency have constrained their further applications. In this study, we fabricated high explosives based nano-boron microspheres with uniform size using the electrostatic spray method, in which the boron nanoparticles and high explosives (CL-20 or PETN) are closely bonded together by fluorinated polymer (F-2602) and evenly distributed. The results indicated that the microspheres exhibited high sphericity and showed an enhanced antioxidant capability. The addition of high-energy explosives not only reduced the thermal oxidation temperature of nano-boron powder within the microspheres but also significantly enhanced the pressurization rate. Additionally, the microspheres with added high-energy explosives released more energy during the combustion process. Compared to physically mixed samples, electrostatically sprayed microspheres with a uniform microstructure still exhibited higher reactivity. Therefore, the design and synthesis of microspheres with controllable structures using the electrostatic spray method show promising application prospects. (c) 2024 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Nano-boron CL-20 PETN Electrospraying Ignition and combustion NANOPARTICLES COMBUSTION

Optimizing multi-parameter distributed fiber sensors:a hybrid Rayleigh-Brillouin-Raman System approach

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Light(Science & Applications) 2024年第3期13卷 393-395页

作者： Kwang Yong song Dept.of Physics Chung-Ang University84 Heukseok-roDongjak-guSeoul 06974Korea

An optimized single-end hybrid Rayleigh,Brillouin,and Raman distributed fiber sensing system has been developed for simultaneous measurement of multiple *** system integrates 3-bit pulse coding for the Raman signal and the Brillouin amplification of the Rayleigh-backscattered signal,discriminating strain,temperature,and vibration using a single sensing fiber.

关键词： fiber Rayleigh signal

Berry-Esseen bounds for self-normalized sums of locally dependent random variables

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Science China Mathematics 2024年第11期67卷 2629-2652页

作者： Zhuo-song Zhang Department of Statistics and Data Science Southern University of Science and Technology

The Berry-Esseen bound provides an upper bound on the Kolmogorov distance between a random variable and the normal *** this paper,we establish Berry-Esseen bounds with optimal rates for self-normalized sums of locally dependent random variables,assuming only a second-moment *** proof leverages Stein's method and introduces a novel randomized concentration inequality,which may also be of independent interest for other *** main results have applied to self-normalized sums of m-dependent random variables and graph dependency models.

关键词： Berry-Esseen bounds self-normalized sums localdependence $m$-dependence graph dependency

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Effect of nano-carbon black content on wetting phenomenon of molten steel and alumina-carbon ceramic filter substrates

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Journal of Iron and Steel Research International 2024年第8期31卷 1900-1913页

作者： Jin-wen song Wen Yan Zhe Chen Ying Liu Shao-song Hong The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and TechnologyWuhan 430081HubeiChina National-provincial Joint Engineering Research Center of High Temperature Materials and Lining Technology Wuhan University of Science and TechnologyWuhan 430081HubeiChina Jiangsu Sheng Nai New Materials Co. Ltd.Taizhou 225503JiangsuChina

The effect of nano-carbon black content(O,8 and 12 wt.%)on the wettability of molten steel on Al_(2)O_(3)-C substrates was investigated by the sessile drop wetting method at 1500℃ under argon *** the beginning of the wetting experiment,the contact angle decreased with the increase in nano-carbon black *** the wetting experiment progressed,FeAl_(2)0_(4) layer and sheet Al_(2)O_(3) layer were found at the interface between the molten steel and the Al_(2)O_(3)-C substrates with O and 8 wt.% nano-carbon black content,and the contact angle deceased with *** the content of nano-carbon black was 12 wt.%,a large number of nano-Al_(2)O_(3) whiskers were observed,which made the contact angle between the molten steel and Al_(2)O_(3)-C substrate become *** on the scanning electron microscope and energy dispersive spectrometry results,the formation mechanism of FeAl2O4 layer and Al_(2)O_(3) layer and the interfacial reaction mechanism were proposed.

关键词： Contact angle Nano-carbon black Al_(2)O_(3)-C substrate Molten steel Interfacial reaction

含光伏的油田综合能源系统的热电厂和需求响应协同调峰能力分析

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电力自动化设备 2022年第7期42卷 198-204页

作者：王艳松宋阳阳倪承波衣京波邹璞中国石油大学(华东)新能源学院山东青岛266580 胜利石油管理局经营管理处山东东营257087 胜利石油管理局胜利发电厂山东东营257087

大规模发展可再生能源是构建低碳可持续能源系统的重要保障,源-荷协同调峰是消纳可再生能源的有效途径。为此,研究含光伏的油田综合能源系统的热电厂和需求响应协同调峰,分析冬季典型场景下的热电厂热电耦合机理,建立热电耦合调峰约束;... 详细信息

大规模发展可再生能源是构建低碳可持续能源系统的重要保障,源-荷协同调峰是消纳可再生能源的有效途径。为此,研究含光伏的油田综合能源系统的热电厂和需求响应协同调峰,分析冬季典型场景下的热电厂热电耦合机理,建立热电耦合调峰约束;针对油田综合负荷的用能特性和分布式光伏发电的特点,建立负荷集群的用电数学模型和用热数学模型,考虑热电机组、负荷响应及源-荷系统运行技术约束,以油田全局能耗成本最小为目标建立自备热电厂和需求响应协同调峰优化模型,制定油田电网源-荷协同调峰策略,通过循环寻优求解源-荷协同最大调峰能力。算例分析表明,源-荷协同光伏发电调峰能有效地提高油田电网对光伏发电的消纳能力,供暖负荷的需求响应使冬季热电厂“以热定电”的刚性约束弹性化,调峰贡献度在需求响应中占比最大。

关键词：油田综合能源自备热电厂光伏发电需求响应源-荷协同调峰能力

Spiking neural networks in intelligent control systems:a perspective

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Science China(Information Sciences) 2024年第7期67卷 324-326页

作者： Anguo ZHANG Yongduan song School of Artificial Intelligence Anhui University School of Automation Chongqing University

Artificial intelligence (AI) has undergone substantial advancements in recent years, prompting an era of innovation in various domains. Among the groundbreaking contributions, neural networks stand at the forefront, powering applications ranging from computer vision and natural language processing to intelligent control systems [1, 2].

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Genome-wide SNP markers provided insights into the reproductive strategy and genetic diversity of the green tide causative species Ulva prolifera in China

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Journal of Oceanology and Limnology 2024年第2期42卷 533-543页

作者： song SUN Weiwei MA Nan WANG song FENG Yan SUN CAS Key Laboratory of Marine Ecology and Environmental Sciences Institute of OceanologyChinese Academy of SciencesQingdao 266071China Laboratory for Marine Ecology and Environmental Science Laoshan LaboratoryQingdao 266237China Jiaozhou Bay Marine Ecosystem Research Station Chinese Academy of SciencesQingdao 266071China University of Chinese Academy of Sciences Beijing 100049China

Ulva prolifera is the causative species of the annually occurring large-scale green tides in China since *** specific biological features on reproductivity strategies,as well as intra-species genetic diversity,are still largely unknown,especially at the genome level,despite their importance in understanding the formation and outbreak of massive green *** the present study,the restriction site-associated DNA genotyping approach(2b-RAD)was adopted to identify the genome-wide single-nucleotide polymorphisms(SNPs)of 54 individual thalli including samples collected from Subei Shoal in 2019 and Qingdao coast from 2019 to *** genotype results revealed that most of the thalli in 2019 and 2020 were haploid gametophytes,while only half of the thalli were gametophytes in 2021,indicating flexibility in the reproductive strategies for the formation of the green tides among different years and the dominance of asexual and vegetative reproductive mode for the floating ***,population analysis was conducted,and it revealed a very low genetic diversity among samples from Subei Shoal and the Qingdao coast in the same year and a higher divergence among samples in different *** results showed the efficiency of 2b-RAD in the exploration of SNPs in *** and provided the first genome-wide scale evidence for the origin of the large-scale green tides on the Qingdao *** study improved our understanding of the reproductive strategy and genetic diversity of the green tide causative species and will help further reveal the biological causes of the green tide in China.

关键词： green tide Ulva prolifera 2b-RAD single-nucleotide polymorphism(SNP) reproductive strategy genetic diversity

Experimental study on combustion characteristics of supersonic combustor based on alternating-wedge strut

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Chinese Journal of Aeronautics 2024年第5期37卷 214-227页

作者： Jie LI Wenyan song Yuhang WANG School of Power Energy Northwestern Polytechnical UniversityXi’an 710129China

Acetone Planar Lase-Induced Fluorescence(PLIF)and OH-PLIF were employed to capture the fuel distribution and OH distribution downstream for the supersonic combustor based on the alternating-wedge *** combustion establishment process and combustion mode in the combustor under different fuel injection methods and different equivalence ratios were *** with the kerosene-PLIF and OH-PLIF results in the cavity combustor,a comparative analysis was conducted to understand the combustion characteristics and combustion modes between the alternating-wedge strut-based combustor and the cavity-based *** results show that the combustor is in weak combustion mode in the case of low equivalence ratio,and the combustor is in intensive combustion mode in the case of high equivalence *** lower limit of the equivalence ratio of the combustor to maintain the intensive combustion mode varies based on different fuel injection *** OH distribution under reacting condition has a strong correlation with the fuel distribution under non-reacting *** OH fluorescence signal near the injector is weaker when the fuel distribution is more *** injector position located at the base of the strut rear has better mixing performance,enabling the combustor to be in intensive combustion mode at a lower equivalence *** combustion reaction in the alternating-wedge strut-based combustor is not necessarily dominated by mass transfer due to the mixing enhancement and premixed zone downstream of strut,while the combustion reaction process in the cavity-based combustor is mainly influenced by mass transfer.

关键词： Supersonic combustor Alternating-wedge strut Cavity PLIF Fuel injection Fuel distribution Combustion characteristics Combustion mode

A credible traffic prediction method based on self-supervised causal discovery

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Science China(Information Sciences) 2024年第5期67卷 244-258页

作者： Dan WANG Yingjie LIU Bin song State Key Laboratory of Integrated Services Networks Xidian University

Next-generation wireless network aims to support low-latency, high-speed data transmission services by incorporating artificial intelligence(AI) technologies. To fulfill this promise, AI-based network traffic prediction is essential for pre-allocating resources, such as bandwidth and computing power. This can help reduce network congestion and improve the quality of service(QoS) for users. Most studies achieve future traffic prediction by exploiting deep learning and reinforcement learning, to mine spatio-temporal correlated variables. Nevertheless, the prediction results obtained only by the spatio-temporal correlated variables cannot reflect real traffic changes. This phenomenon prevents the true prediction variables from being inferred, making the prediction algorithm perform poorly. Inspired by causal science, we propose a novel network traffic prediction method based on self-supervised spatio-temporal causal discovery(SSTCD). We first introduce the Granger causal discovery algorithm to build a causal graph among prediction variables and obtain spatio-temporal causality in the observed data, which reflects the real reasons affecting traffic ***, a graph neural network(GNN) is adopted to incorporate causality for traffic prediction. Furthermore,we propose a self-supervised method to implement causal discovery to to address the challenge of lacking ground-truth causal graphs in the observed data. Experimental results demonstrate the effectiveness of the SSTCD method.

关键词： wireless network traffic prediction causal discovery self-supervised